Digital video recorders (DVR) allow a convenient and flexible way of storing and retrieving video and audio information accessible to the modern user of media content. Today, the majority of video content is coming from cable or satellite providers, or archived on different media. However, the rapid development of broadband networks will increase the percentage of content coming from the Internet, peer-to-peer sharing, etc. These trends blur the traditional concept of channels and we therefore refer to the possible sources of video as the ocean of content.
Storing and retrieving important content from this ocean is becoming a problem. Given the large choice of content, the user has problems choosing what he wants to see. Assuming that a typical DVR can store hours of video, a typical, modern user who has limited time is unable to see even a small fraction of the data he would like to see. Modern DVRs have some basic capabilities facilitating the preview and retrieval of recorder content, but they are too limited and generic to be convenient.
Viewers of video typically desire the ability to see certain portions of a program that are significant to them (i.e., desired content). It should be understood that for a single content, multiple different video digests can be created, depending upon the definition of desired and undesired content. Since such definitions are subjective, ideally, a video digest is custom-tailored for every user.
Theoretically, desired and undesired content can be given a semantic description. For example, one may wish to see scenes of car crashes and exclude advertisements. “Car crashes” and “advertisements” are semantic labels to the aforementioned classes of video content. Matching of semantic description to video content belongs to the general category of pattern recognition problems, usually referred to as video search. As of today's state of science and technology, there are no unique and reliable ways to relate high-level semantic description to the actual video content. The major distinction between video digest and video search applications is that in video digest, the user does not wish to describe semantically the content he would like or would not like to see, and usually prefers a zero-effort experience, in which no explicit interaction with the system is needed.